基于小波域统计混合模型的图像降噪方法

易翔; 王蔚然

基于小波域统计混合模型的图像降噪方法

易翔,
王蔚然

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出版历程
- 收稿日期: 2004-04-28
- 修回日期: 2004-12-30
- 刊出日期: 2005-11-19

Method of Image Denoising Based on Statistical Mixture Model in Wavelet Domain

摘要

摘要: 该文提出了一种基于小波域统计混合模型的图像降噪方法。该方法首先利用尺度间模型，将小波系数分成两类：有意义系数和无意义系数；然后在小波域同层模型中运用最大后验概率估计方法，从有意义系数中恢复出原始系数。文章给出了算法的完整步骤。实验结果及分析表明了该方法的有效性。
- 小波变换; 最大后验概率; 混合模型; 图像降噪
Abstract: In this paper, a novel image denoising method based on statistical mixture model in wavelet domain is proposed. Firstly, the wavelet coefficients are classified as significant and insignificant coefficients by using interscale statistical model. Secondly, Maximum A Posteriori (MAP) estimator based on intrascale statistical model is used to restore the noisy wavelet image coefficients. A completive algorithm is presented to implement this idea. Experimental results and analysis are given to demonstrate the validity and effectiveness of the proposed method.

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Chang S, Yu B, Vetterli M. Adaptive wavelet thresholding for image denoising and compression[J].IEEE Trans. on Image Processing.2000, 9(9):1532-1546[2]Crouse M S, Nowak R D. Wavelet-based signal processing using hidden Markov models[J].IEEE Trans. on Signal Processing.1998, 46(4):886-902[3]Lewis A S, Knowles G. Image compressing using the 2-d wavelet transform. IEEE Trans. on Image Processing, 1992, 1(2): 224-250.[4]Liu J, Moulin P. Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients[J].IEEE Trans. on Image Processing.2001, 10(11):1647-1658[5]Simoncelli E P, Adelson E H. Noise removal via Bayesian wavelet coring. In Proc. IEEE Int. Conf. on Image Processing, Lausanne, Switzerland, 1996, 1: 379-382.[6]Donoho D L, Johnstone I M. Ideal spatial adaptation via wavelet shrinkage[J].Biometrika.1994, 81(3):425-455[7]Donoho D L, Johnstone I M. Adapting to unknown smoothness[8]via wavelet shrinkage. Journal of American Statistical Assoc., 1995, 90(432): 1200-1224.[9]Rombery J K.[J].Choi H, Baraniuk R G. Hidden Markov tree modeling of complex wavelet transforms. In Proc. IEEE ICASSP 00, Istanbul, Turkey.2000,:-[10]Kingsbury N G. The dual-tree complex wavelet transform: a new efficient tool for image restoration and enhancement. In Proc. EUSIPCO 98, Island of Rhodes, Greek, 1998: 319-322.[11]Kingsbury N G. A dual-tree complex wavelet transform with improved orthogonality and symmetry properties. In Proc. IEEE Int. Conf. on Image Processing, Vancouver, Canada, 2000, 2: 375-378.[12]Sendur I, Selesnick I W. Bivariate shrinkage function for wavelet-based denoising exploiting interscale dependency[J].IEEE Trans. on Signal Processing.2002, 50(11):2744-2756

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